5 Hot Big Data Startups
These five Big Data startups are attracting the interest of investors and potential customers.
Big Data is one of the hottest areas of IT right now. Analyst firm International Data Corp. (IDC) predicts that the Hadoop and Big Data markets will have a compound annual growth rate of 54.9 percent through 2017 – and that’s on top of already explosive growth over the last few years.
The market acceleration is reflected in the large number of startups that are popping up in the Big Data analytics field. They are rushing to market with a varied set of architectures that simplify and/or speed up the process of analyzing vast quantities of information and providing insight to enterprises in real time.
Here are a few of the more interesting new kids on the block in Big Data analytics.
Glassbeam promotes itself as a specialist in multi-structured machine data analytics. It offers apps for customer support, product development and sales, based an element known as Semiotic Parsing Language (SPL) that extracts added intelligence from machine data. The company recently received an additional injection of $3 million in funding from VKRM Group.
"The machine data analytics market is poised to take off as more and more companies wire their products to phone-home data," said Srikanth Desikan, vice president of Products for Glassbeam. "This data can be used strategically for product and service improvements as well as provide enhanced services to customers."
DataRPM uses natural language as part of search-based Big Data analytics. Users ask questions in natural language to enable them to analyze their data with no coding or SQL required. It can be embedded into apps, blogs, websites and portals. The company prices its technology per server node, dependent on how much data is being used.
Still in beta mode, DataRPM plans to bring a defined product to the market in 2014's first quarter. So far, the biggest interest has come from information service providers (ISVs), hardware and software companies and software-as-a-service (SaaS) providers. A modest seed round of funding produced $800,000, from CIT GAP Funds, 20K Industries and a few other angel investors. Another round of funding is planned in 2014.
"DataRPM’s Instant Answers technology is the only embeddable Big Data visualization and natural language analytics platform built on computational search technology." said Sundeep Sanghavi, DataRPM's CEO and co-founder. "You speak or type your questions, and the platform delivers a visualization from any size data set, anytime, anywhere and is available in the cloud, private cloud and on-premise."
Treasure Data provides a cloud service which helps businesses get value from Big Data by simplifying the process of data collection, storage and analysis. The company says its service is secure and easy to set up. The whole point is to allow organizations to process enormous amounts of real-time data, including Web, application, mobile, log, sensor and machine data.
Its clients are grouped mainly in advertising, digital marketing, social, mobile, gaming and automotive. The company received $5 million in funding this year from Sierra Ventures.
"The new economy of the cloud will transform Big Data as it has storage, collaboration and CRM," said Hiro Yoshikawa, co-founder and CEO of Treasure Data. "Customers use our cloud services for the testing of Big Data projects on short timelines, measuring business areas in new ways, scaling projects that work and folding projects that don’t."
Phu Hoang, CEO and co-founder at DataTorrent, characterizes his company as a real-time computation platform for Big Data. Hoang is a 12-year Yahoo veteran, formerly serving as executive vice president of Engineering.
The company’s product enables businesses to monitor, analyze and act on large amounts of structured and unstructured data. As a native Hadoop platform, DataTorrent can leverage an existing Hadoop infrastructure. The company raised $8 million in funding by the likes of August Capital, Morado Venture Partners and Yahoo.
Alpine Data Labs
Alpine Data Labs is also focusing on analytics, but this time on the predictive side. It just ended a $16 million round of Series B funding to finance its Big Data ambitions. Investors include Sierra Ventures, Mission Ventures, UMC Capital and Robert Bosch Venture Capital GmbH.
Joe Otto, CEO of Alpine, said his company has created a software architecture that takes advantage of the storage and compute power of Hadoop and databases like Greenplum. Essentially, Alpine enables complex algorithms to run on top of large data systems without having to move data around or engage in complex coding. Customers include Sony, Nike, Barclay's, Equifax and Kaiser Permanente.
Drew Robb is a freelance writer specializing in technology and engineering. Currently living in California, he is originally from Scotland, where he received a degree in geology and geography from the University of Strathclyde. He is the author of Server Disk Management in a Windows Environment (CRC Press).